Difference between revisions of "Template:Article of the week"

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Fuertes GIMDS2018 7-1.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Karaattuthazhathu NatJLabMed23 12-2.png|260px]]</div>
'''"[[Journal:CÆLIS: Software for assimilation, management, and processing data of an atmospheric measurement network|CÆLIS: Software for assimilation, management, and processing data of an atmospheric measurement network]]"'''
'''"[[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study]]"'''


Given the importance of atmospheric aerosols, the number of instruments and measurement networks which focus on its characterization is growing. Many challenges are derived from standardization of protocols, monitoring of instrument status to evaluate network [[Data integrity|data quality]], and manipulation and distribution of large volumes of data (raw and processed). CÆLIS is a software system which aims to simplify the management of a network, providing the scientific community a new tool for monitoring instruments, processing data in real time, and working with the data. Since 2008, CÆLIS has been successfully applied to the photometer calibration facility managed by the University of Valladolid, Spain, under the framework of the Aerosol Robotic Network (AERONET). Thanks to the use of advanced tools, this facility has been able to analyze a growing number of stations and data in real time, which greatly benefits network management and data quality control. The work describes the system architecture of CÆLIS and gives some examples of applications and data processing. ('''[[Journal:CÆLIS: Software for assimilation, management, and processing data of an atmospheric measurement network|Full article...]]''')<br />
For the release of precise and accurate reports of [[Medical test|routine tests]], its necessary to follow a proper [[quality management system]] (QMS) in the [[clinical laboratory]]. As one of the most popular QMS tools for process improvement, Six Sigma techniques and tools have been accepted widely in the [[laboratory]] testing process. Six Sigma gives an objective assessment of analytical methods and instrumentation, measuring the outcome of a process on a scale of 0 to 6. Poor outcomes are measured in terms of defects per million opportunities (DPMO). To do the performance assessment of each clinical laboratory [[analyte]] by Six Sigma analysis and to plan and chart out a better, customized [[quality control]] (QC) plan for each analyte, according to its own sigma value ... ('''[[Journal:Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study|Full article...]]''')<br />
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Latest revision as of 16:52, 29 April 2024

Fig1 Karaattuthazhathu NatJLabMed23 12-2.png

"Sigma metrics as a valuable tool for effective analytical performance and quality control planning in the clinical laboratory: A retrospective study"

For the release of precise and accurate reports of routine tests, its necessary to follow a proper quality management system (QMS) in the clinical laboratory. As one of the most popular QMS tools for process improvement, Six Sigma techniques and tools have been accepted widely in the laboratory testing process. Six Sigma gives an objective assessment of analytical methods and instrumentation, measuring the outcome of a process on a scale of 0 to 6. Poor outcomes are measured in terms of defects per million opportunities (DPMO). To do the performance assessment of each clinical laboratory analyte by Six Sigma analysis and to plan and chart out a better, customized quality control (QC) plan for each analyte, according to its own sigma value ... (Full article...)
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